Workshop in Biostatistics
|DATE:||April 21, 2016|
|TIME:||1:30 - 3:00 pm|
|LOCATION:||Medical School Office Building, Rm x303|
|TITLE:||Statistical Methods for Single-Cell Gene Expression Data|
The growing use of single-cell gene expression data offers insight both into normal cellular function and into diseases such as cancer, but single-cell data presents new challenges which standard clustering and dimensionality reduction methods are not designed to confront. We show that performance of standard algorithms suffers on single-cell data and present several new models which yield better performance on both simulated and biological data.
Emma Pierson and Christopher Yau. ZIFA: Dimensionality reduction for zero-inflated single-cell gene expression analysis. Genome Biology 2015, 16:241.